Ultra-Fast Reservoir Characterisation and Well-Performance Evaluation Enabled by Digital Permeability Twins

Industry practice for forecasting production rates of oil and gas wells is traditionally split between complex, physics-based simulators and empirical decline-curve analysis (DCA). Recently developed digital permeability twins coupled with closed-form Gaussian production models bridge the gap by offering a fast, physics-based alternative that avoids the over-parameterisation of numerical simulators while staying clear of the oversimplifications typical for purely empirical DCA approaches. Onshore and offshore case studies show that robust, production forecasts, well-design optimisation, and SPE compliant reserves classification can be achieved prior to drilling or history-matching limited production data (as little as one month). Applicable across diverse well and reservoir systems, fast decision-making is enabled through probabilistic well-performance forecasting, real-time and pre-drilling, while accurately representing the uncertainty in available data. Gaussian well-performance and resource evaluation thus provides a powerful new option for production analysis and reserves estimation under uncertainty, supporting optimisation efforts and enabling faster field-development decision-making without comprising accuracy.